Multi-Agent Communication with the A2A Python SDK

5 Essential Tweaks That Will Make Your Charts Accessible to Individuals with Visible Impairments

The Function of Luck in Sports activities: Can We Measure It?

If underneath a rock and you’re employed with AI, you’ve in all probability heard about Agent2Agent (A2A) Protocol, “an open commonplace designed to allow communication and collaboration between AI Brokers”. It’s nonetheless fairly new, but it surely’s already getting numerous buzz. Because it performs so properly with MCP (which appears prefer it’s changing into the business’s commonplace), A2A is shaping as much as be the go-to commonplace for multi-agent communication within the business.

When Google first dropped the Protocol Specification, my first response was principally: “Okay, cool… however what am I presupposed to do with this?” Fortunately, this week they launched the official Python SDK for the protocol, so now it lastly speaks a language I perceive.

On this article we’re going to dive into how the protocol truly units up communication between brokers and purchasers. Spoiler: it’s all in a task-oriented method. To make issues much less summary, let’s construct a bit of toy instance collectively.

Communication between the Occasion Detector Agent and an A2A Shopper

In our programs we now have an Occasion Detector AI Agent (chargeable for detecting occasions) and an Alert AI Agent (chargeable for alerting the consumer of the occasions). Since I’m specializing in the A2A protocol right here, each brokers are mocked as easy Python strategies that return strings. However in actual life you may construct your brokers with any framework you want (LangGraph, Google ADK, CrewAI and so forth).

We’ve got three characters in our system, the consumer, the Occasion Agent and the Alert Agent. All of them talk utilizing Messages. A Message represents a single flip of communication within the A2A protocol. We wrap the brokers into A2A Servers. The servers expose an HTTP endpoint implementing the protocol. Every A2A Server has Occasion queues that act as a buffer between the agent’s asynchronous execution and the server’s response dealing with.

The A2A Shopper initiates communication, and if two brokers want to speak an A2A Server may play the function of a A2A Shopper. The diagram beneath exhibits how a Shopper and a Server talk inside the protocol.

The EventQueue shops Messages, Duties, TaskStatusUpdateEvent, TaskArtifactUpdateEvent, A2AError and JSONRPCError objects. The Job is perhaps an important object to grasp construct multi-agent programs with A2A. In accordance with the A2A documentation:

When a consumer sends a message to an agent, the agent may decide that fulfilling the request requires a stateful process to be accomplished (e.g., “generate a report,” “guide a flight,” “reply a query”).
Every process has a singular ID outlined by the agent and progresses by an outlined lifecycle (e.g., submitted, working, input-required, accomplished, failed).
Duties are stateful and might contain a number of exchanges (messages) between the consumer and the server.

Consider a Job as one thing in your multi-agent system that has a clear and distinctive objective. We’ve got two duties in our system:

Detect an occasion
Alert the consumer

Every Agent does its personal factor (process). Let’s construct the A2A Server for the Occasion Agent so issues change into extra tangible.

Constructing the A2A Server for the Occasion Agent

First up: the Agent Card. The Agent Card is JSON doc used to get to know different brokers out there. :

Server’s id
Capabilities
Expertise
Service endpoint
URL
How purchasers ought to authenticate and work together with the agent

Let’s first outline the Agent Card for the Occasion Detector AI Agent (I’ve outlined the abilities based mostly on this instance from Google):

agent_card = AgentCard(  
    title='Occasion Detection Agent',  
    description='Detects related occasions and alerts the consumer',  
    url='http://localhost:10008/',  
    model='1.0.0',  
    defaultInputModes=['text'],  
    defaultOutputModes=['text'],  
    capabilities=AgentCapabilities(streaming=False),  
    authentication={ "schemes": ["basic"] },  
    expertise=[  
        AgentSkill(  
            id='detect_events',  
            name='Detect Events',  
            description='Detects events and alert the user',  
            tags=['event'],  
        ),  
    ],  
)

You may study extra in regards to the Agent Card object construction right here: https://google.github.io/A2A/specification/#55-agentcard-object-structure

The agent itself will truly be a Uvicorn server, so let’s construct the primary() technique to get it up and operating. All of the request might be dealt with by the DefaultRequestHandler of the a2a-python SDK. The handler wants a TaskStore to retailer the Duties and an AgentExecutor which has the implementation of the core logic of the agent (we’ll construct the EventAgentExecutor in a minute).

The final part of the primary() technique is the A2AStarletteApplication, which is the Starlette utility that implements the A2A protocol server endpoints. We have to present the Agent Card and the DefaultRequestHandler to initialize it. Now the final step is to run the app utilizing uvicorn. Right here is the complete code of the primary() technique:

import click on  
import uvicorn  
from a2a.sorts import (  
    AgentCard, AgentCapabilities, AgentSkill
) 
from a2a.server.request_handlers import DefaultRequestHandler  
from a2a.server.duties import InMemoryTaskStore  
from a2a.server.apps import A2AStarletteApplication 
 
@click on.command()  
@click on.choice('--host', default='localhost')  
@click on.choice('--port', default=10008)  
def primary(host: str, port: int):  
    agent_executor = EventAgentExecutor()

    agent_card = AgentCard(  
        title='Occasion Detection Agent',  
        description='Detects related occasions and alerts the consumer',  
        url='http://localhost:10008/',  
        model='1.0.0',  
        defaultInputModes=['text'],  
        defaultOutputModes=['text'],  
        capabilities=AgentCapabilities(streaming=False),  
        authentication={ "schemes": ["basic"] },  
        expertise=[              AgentSkill(                  id='detect_events',                  name='Detect Events',                  description='Detects events and alert the user',                  tags=['event'],  
            ),  
        ],  
    )
      
    request_handler = DefaultRequestHandler(  
        agent_executor=agent_executor,  
        task_store=InMemoryTaskStore()  
    ) 
 
    a2a_app = A2AStarletteApplication(  
        agent_card=agent_card,  
        http_handler=request_handler  
    )  

    uvicorn.run(a2a_app.construct(), host=host, port=port)

Creating the EventAgentExecutor

Now it’s time to construct the core of our agent and eventually see use the Duties to make the brokers work together with one another. The EventAgentExecutor class inherits from AgentExecutor interface and thus we have to implement the execute() and the cancel() strategies. Each take a RequestContext and an EventQueue object as parameters. The RequestContext holds details about the present request being processed by the server and the EventQueue acts as a buffer between the agent’s asynchronous execution and the server’s response dealing with.

Our agent will simply test if the string “occasion” is within the message the consumer have despatched (KISS ). If the “occasion” is there then we should always name the Alert Agent. We’ll try this by sending a Message to this different Alert agent. That is the Direct Configuration technique, which means we’ll configure the agent with a URL to fetch the Agent Card of the Alert Agent. To try this our Occasion Agent will act like a A2A Shopper.

Let’s construct the Executor step-by-step. First let’s create the primary Job (the duty to detect the occasions). We have to instantiate a TaskUpdater object (a helper class for brokers to publish updates to a process’s occasion queue), then submit the duty and announce we’re engaged on it with the start_work() technique:

from a2a.server.agent_execution import AgentExecutor

class EventAgentExecutor(AgentExecutor):  
    async def execute(self, context: RequestContext, event_queue: EventQueue):  
        task_updater = TaskUpdater(event_queue, context.task_id, context.context_id)  
        task_updater.submit()  
        task_updater.start_work()

The message the consumer will ship to the agent will seem like this:

send_message_payload = {  
        'message': {  
            'function': 'consumer',  
            'components': [{'type': 'text', 'text': f'it has an event!'}],  
            'messageId': uuid4().hex,  
        }  
    }

A Half represents a definite piece of content material inside a Message, representing exportable content material as both TextPart, FilePart, or DataPart. We’ll use a TextPart so we have to unwrap it within the executor:

from a2a.server.agent_execution import AgentExecutor

class EventAgentExecutor(AgentExecutor):  
    async def execute(self, context: RequestContext, event_queue: EventQueue):  
        task_updater = TaskUpdater(event_queue, context.task_id, context.context_id)  
        task_updater.submit()  
        task_updater.start_work()

        await asyncio.sleep(1) #let's faux we're truly doing one thing

        user_message = context.message.components[0].root.textual content # unwraping the TextPart

Time to create the tremendous superior logic of our agent. If the message doesn’t have the string “occasion” we don’t have to name the Alert Agent and the duty is finished:

from a2a.server.agent_execution import AgentExecutor

class EventAgentExecutor(AgentExecutor):  
    async def execute(self, context: RequestContext, event_queue: EventQueue):  
        task_updater = TaskUpdater(event_queue, context.task_id, context.context_id)  
        task_updater.submit()  
        task_updater.start_work()

        await asyncio.sleep(1) #let's faux we're truly doing one thing

        user_message = context.message.components[0].root.textual content # unwraping the TextPart

        if "occasion" not in user_message:  
            task_updater.update_status(  
                TaskState.accomplished,  
                message=task_updater.new_agent_message(components=[TextPart(text=f"No event detected")]),
            )

Creating an A2A Shopper for the Person

Let’s create an A2A Shopper so we will check the agent as it’s. The consumer makes use of the get_client_from_agent_card_url() technique from A2AClient class to (guess what) get the agent card. Then we wrap the message in a SendMessageRequest object and ship it to the agent utilizing the send_message() technique of the consumer. Right here is the complete code:

import httpx  
import asyncio  
from a2a.consumer import A2AClient  
from a2a.sorts import SendMessageRequest, MessageSendParams  
from uuid import uuid4  
from pprint import pprint
  
async def primary():    
    send_message_payload = {  
        'message': {  
            'function': 'consumer',  
            'components': [{'type': 'text', 'text': f'nothing happening here'}],  
            'messageId': uuid4().hex,  
        }  
    }  

    async with httpx.AsyncClient() as httpx_client:  
        consumer = await A2AClient.get_client_from_agent_card_url(  
            httpx_client, 'http://localhost:10008'  
        )  
        request = SendMessageRequest(  
            params=MessageSendParams(**send_message_payload)  
        )  
        response = await consumer.send_message(request)  
        pprint(response.model_dump(mode='json', exclude_none=True))  
  
if __name__ == "__main__":  
    asyncio.run(primary())

That is what occurs within the terminal that’s operating the EventAgent server:

And that is the message the consumer sees:

The duty to detect the occasion was created and no occasion was detected, good! However the entire level of A2A is to make Brokers talk with one another, so let’s make the Occasion Agent speak to the Alert Agent.

Making the Occasion Agent speak to the Alert Agent

To make the Occasion Agent speak to the Alert Agent the Occasion Agent will act as a consumer as effectively:

from a2a.server.agent_execution import AgentExecutor

ALERT_AGENT_URL = "http://localhost:10009/" 

class EventAgentExecutor(AgentExecutor):  
    async def execute(self, context: RequestContext, event_queue: EventQueue):  
        task_updater = TaskUpdater(event_queue, context.task_id, context.context_id)  
        task_updater.submit()  
        task_updater.start_work()

        await asyncio.sleep(1) #let's faux we're truly doing one thing

        user_message = context.message.components[0].root.textual content # unwraping the TextPart

        if "occasion" not in user_message:  
            task_updater.update_status(  
                TaskState.accomplished,  
                message=task_updater.new_agent_message(components=[TextPart(text=f"No event detected")]),
            )
        else:
            alert_message = task_updater.new_agent_message(components=[TextPart(text="Event detected!")])

            send_alert_payload = SendMessageRequest(  
                params=MessageSendParams(  
                    message=alert_message  
                )  
            )  

            async with httpx.AsyncClient() as consumer:  
                alert_agent = A2AClient(httpx_client=consumer, url=ALERT_AGENT_URL)  
                response = await alert_agent.send_message(send_alert_payload)  

                if hasattr(response.root, "outcome"):  
                    alert_task = response.root.outcome  
                    # Polling till the duty is finished
                    whereas alert_task.standing.state not in (  
                        TaskState.accomplished, TaskState.failed, TaskState.canceled, TaskState.rejected  
                    ):  
                        await asyncio.sleep(0.5)  
                        get_resp = await alert_agent.get_task(  
                            GetTaskRequest(params=TaskQueryParams(id=alert_task.id))  
                        )  
                        if isinstance(get_resp.root, GetTaskSuccessResponse):  
                            alert_task = get_resp.root.outcome  
                        else:  
                            break  
  
                    # Full the unique process  
                    if alert_task.standing.state == TaskState.accomplished:  
                        task_updater.update_status(  
                            TaskState.accomplished,  
                            message=task_updater.new_agent_message(components=[TextPart(text="Event detected and alert sent!")]),  
                        )  
                    else:  
                        task_updater.update_status(  
                            TaskState.failed,  
                            message=task_updater.new_agent_message(components=[TextPart(text=f"Failed to send alert: {alert_task.status.state}")]),  
                        )  
                else:  
                    task_updater.update_status(  
                        TaskState.failed,  
                        message=task_updater.new_agent_message(components=[TextPart(text=f"Failed to create alert task")]),  
                    )

We name the Alert Agent simply as we known as the Occasion Agent because the consumer, and when the Alert Agent process is finished, we full the unique Occasion Agent process. Let’s name the Occasion Agent once more however this time with an occasion:

The sweetness right here is that we merely known as the Alert Agent and we don’t have to know something about the way it alerts the consumer. We simply ship a message to it and watch for it to complete.

The Alert Agent is tremendous much like the Occasion Agent. You may test the entire code right here: https://github.com/dmesquita/multi-agent-communication-a2a-python

Ultimate Ideas

Understanding construct multi-agent programs with A2A is perhaps daunting at first, however in the long run you simply ship messages to let the brokers do their factor. All you should do to combine you brokers with A2A is to create a category with the agent’s logic that inherit from the AgentExecutor and run the agent as a server.

I hope this text have helped you in your A2A journey, thanks for studying!